Description Usage Arguments Value Author(s) See Also Examples
Bivariate normal prediction regions are added to a lattice panel.
1 2 | cnPredictionPanel(x, y, ..., object, copynumber, x.axis, line.col,
line.lwd, shades, subscripts, data.last =FALSE, highlight.index = NULL, scale.sd = rep(1, 2))
|
x |
passed to panel.xyplot |
y |
passed to panel.xyplot |
... |
passed to panel.xyplot |
object |
object of class |
copynumber |
Integer vector. Which prediction regions to plot. |
x.axis |
valid entries are 'A' or 'B', indicating whether the A or B allele is to be plotted on the x-axis. |
line.col |
the color for the border of the prediction regions |
line.lwd |
currently ignored |
shades |
the fill color for the prediction regions |
subscripts |
passed to panel.xyplot |
data.last |
whether to plot the data before or after plotting the prediction regions |
highlight.index |
an integer vector. If not missing, this vector can be used to highlight the position of some samples in the A vs B scatterplot. These samples will be plotted with an 'X' instead of an 'o'. |
scale.sd |
whether to scale the A and B standard deviations to provide a sample specific prediction region. This is experimental and defaults to 1 (no scaling) |
a lattice object
R. Scharpf
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | library("crlmm")
library("crlmmCompendium")
###################################################
### chunk number 27: loadObject-exampleData1
###################################################
#line 1164 "manuscript.Rnw"
data(exampleData1)
###################################################
### chunk number 30: defineLatticeObjects
###################################################
#line 1223 "manuscript.Rnw"
ldat <- prePredictPanel(exampleData1)
shades <- makeTransparent(brewer.pal(6, "BrBG"), alpha=0.6)[c(1,2,3,5,6)]
##replace the middle color (white) with something else
mykey <- simpleKey(as.character(0:4), points=FALSE, rectangles=TRUE, col="black", space="right", cex=0.7)
mykey$rectangles[["col"]] <- shades
fig2 <- xyplot(A~B|snp, ldat, cex=0.3, panel=cnPredictionPanel, object=exampleData1,
x.axis="B", copynumber=0:4, line.col=shades, line.lwd=1.5,
shades=shades, ylab=expression(log[2](I[A])), xlab=expression(log[2](I[B])),
par.strip.text=list(lines=0.9, cex=0.6),
key=mykey)
###################################################
### chunk number 31: ABscatterplots
###################################################
#line 1237 "manuscript.Rnw"
pars <- trellis.par.get()
pars$axis.text$cex <- 0.3
pars$xlab.text$cex <- 0.8
trellis.par.set("axis.text", pars$axis.text)
trellis.par.set("axis.text", pars$xlab.text)
print(fig2)
|
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